Open Access

ARTICLE

Computational Analysis of Airflow in Upper Airway under Light and Heavy Breathing Conditions for a Realistic Patient Having Obstructive Sleep Apnea

W. M. Faizal^1,2, N. N. N. Ghazali^2,*, C. Y. Khor¹, M. Z. Zainon², Irfan Anjum Badruddin^3,4,*, Sarfaraz Kamangar⁴, Norliza Binti Ibrahim⁵, Roziana Mohd Razi⁶

1 Faculty of Mechanical Engineering Technology, University Malaysia Perlis, Perlis, Malaysia
2 Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia
3 Research Center for Advanced Materials Science, King Khalid University, Abha, 61413, Saudi Arabia
4 Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
5 Department of Oral & Maxillofacial Clinical Science, Faculty of Dentistry, University of Malaya, Kuala Lumpur, 50603, Malaysia
6 Department of Paediatric Dentistry and Orthodontics, Faculty of Dentistry, University of Malaya, Kuala Lumpur, 50603, Malaysia

* Corresponding Authors: N. N. N. Ghazali. Email: nik ; Irfan Anjum Badruddin. Email:

Computer Modeling in Engineering & Sciences 2021, 128(2), 583-604. https://doi.org/10.32604/cmes.2021.015549

Received 26 December 2020; Accepted 20 April 2021; Issue published 22 July 2021

Abstract

Background: Obstructive sleep apnea is a sleeping disorder that has troubled a sizeable population. There is an active area of research on obstructive sleep apnea that intends to better understand airflow behaviors and therefore treat patients more effectively. This paper aims to investigate the airflow characteristics of the upper airway in an obstructive sleep apnea (OSA) patient under light and heavy breathing conditions by using Turbulent Kinetic Energy (TKE), an accurate method in expressing the flow concentration mechanisms of sleeping disorders. It is important to visualize the concentration of flow in the upper airway in order to identify the severity level of the obstruction during sleep. Methods: Computational fluid dynamic (CFD) analysis was used as a solution tool to evaluate the airflow during light and heavy breathing conditions. A medical imaging technique was used to extract the 3D model from the CT scan images. Additionally, mesh generation and simulation were carried out via CFD software to evaluate the light and heavy breathing characteristics related to obstructive sleep apnea. Steady state Reynold’s averaged Navier-Stoke (RANS) with the k-ω shear stress transport (SST) turbulence model was utilized. The airflow characteristics were quantified using parameters such as pressure distribution, skin friction coefficient, velocity profile, Reynolds number, turbulent Reynolds number and turbulence kinetic energy. Results: Contour plots at different planes were used to visualize the airflow distribution as it passed through different cross-sectional areas of the airway. The results revealed that the presence of a smaller cross-sectional area of the airway caused an increase in airflow parameters, especially during heavy breathing. Furthermore, turbulent airflow conditions along the airway were noticed during heavy breathing. The severity of OSA could be measured by the turbulent kinetic energy which is able to show the behavior and concentration of mean flow. This study is expected to provide crucial and important results by visualizing the concentration of airflow mechanisms and characteristics of a patient’s airway during light and heavy breathing. These findings enable TKE to be used as a new tool for characterizing the severity of obstructive sleep apnea in the upper airways of patients.

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